Evaluating provincial eco-efficiency in China: an improved network data envelopment analysis model with undesirable output

Intelligent industry, energy regulation and ecological transformation-Taking equity financing as the moderating variable

With the panel data of 21 China's industrial industries from 2008 to 2020, the relationship models between intelligent industry, energy regulation and ecological transformation are constructed and tested from two dimensions of resource saving and environmental friendliness, then equity financing is introduced into this model as moderating variable to discuss the moderating effects on the relationships between intelligent industry, energy regulation and ecological transformation. Results show that: ⑴China's industrial industries significantly transformed to the resource-saving type, and the environment-friendly level stayed in a slow progression. ⑵Intelligent industry affected ecological transformation positively and significantly. The impact of energy regulation on ecological transformation was nonlinear. The regulation of energy consumption can significantly stimulate the transformation of resource saving, and restrain the transformation of environmental friendliness; the regulation of energy structure can significantly stimulate the transformation of environmental friendliness. ⑶ Equity financing can positively moderate the relationship between intelligent industry and ecological transformation, and it can also moderate the regulation of energy structure and promote the transformation to environmental friendliness, especially in the low consumption industries.

Relationship between anthropogenic factors and freshwater quality in Hainan Province, south China

Water resource security directly or indirectly affects the development of society, economy, and the environment, and is of massive significance for regional sustainable development. This study addresses whether anthropogenic activities, especially from tourism, significantly affect the freshwater quality in Hainan Province, China. The freshwater quality in Hainan Province was generally good in 2012 to 2015 (at level II, GB3838-2002). Agriculture, fishery, animal husbandry, and chemical oxygen demand discharge mainly affect freshwater quality in the Nandu and Changhua rivers. Water quality in Wanquan River is more susceptible to tourism in comparison with the Nandu and Changhua rivers. DO content in the Wanquan River fluctuated greatly. It remains necessary to closely monitor negative changes in water quality due to increasing tourism, especially in Wanquan River and eastern Hainan Province. The developed radial basis function neural network shows that the changes in water quality are predicted accurately in comparison with experimental values in the present study. Our results suggested that current anthropogenic factors had a modest effect on water quality on Hainan Island, while tourism had a perceptible effect in eastern Hainan. Our findings provide a reference for the interplay of water quality, people's livelihood, and economic development (tourism and port construction) in Hainan Province.

A network Data Envelopment Analysis to estimate nations' efficiency in the fight against SARS-CoV-2

The ongoing outbreak of SARS-CoV-2 has been deeply impacting health systems worldwide. In this context, it is pivotal to measure the efficiency of different nations' response to the pandemic, whose insights can be used by governments and health authorities worldwide to improve their national COVID-19 strategies. Hence, we propose a network Data Envelopment Analysis (DEA) to estimate the efficiencies of fifty-five countries in the current crisis, including the thirty-seven Organisation for Economic Co-operation and Development (OECD) member countries, six OECD prospective members, four OECD key partners, and eight other countries. The network DEA model is designed as a general series structure with five single-division stages - population, contagion, triage, hospitalisation, and intensive care unit admission -, and considers an output maximisation orientation, denoting a social perspective, and an input minimisation orientation, denoting a financial perspective. It includes inputs related to health costs, desirable and undesirable intermediate products related to the use of personal protective equipment and infected population, respectively, and desirable and undesirable outputs regarding COVID-19 recoveries and deaths, respectively. To the best of the authors' knowledge, this is the first study proposing a cross-country efficiency measurement using a network DEA within the context of the COVID-19 crisis. The study concludes that Estonia, Iceland, Latvia, Luxembourg, the Netherlands, and New Zealand are the countries exhibiting higher mean system efficiencies. Their national COVID-19 strategies should be studied, adapted, and used by countries exhibiting worse performances. In addition, the observation of countries with large populations presenting worse mean efficiency scores is statistically significant.

A network Data Envelopment Analysis to estimate nations' efficiency in the fight against SARS-CoV-2

The ongoing outbreak of SARS-CoV-2 has been deeply impacting health systems worldwide. In this context, it is pivotal to measure the efficiency of different nations' response to the pandemic, whose insights can be used by governments and health authorities worldwide to improve their national COVID-19 strategies. Hence, we propose a network Data Envelopment Analysis (DEA) to estimate the efficiencies of fifty-five countries in the current crisis, including the thirty-seven Organisation for Economic Co-operation and Development (OECD) member countries, six OECD prospective members, four OECD key partners, and eight other countries. The network DEA model is designed as a general series structure with five single-division stages - population, contagion, triage, hospitalisation, and intensive care unit admission -, and considers an output maximisation orientation, denoting a social perspective, and an input minimisation orientation, denoting a financial perspective. It includes inputs related to health costs, desirable and undesirable intermediate products related to the use of personal protective equipment and infected population, respectively, and desirable and undesirable outputs regarding COVID-19 recoveries and deaths, respectively. To the best of the authors' knowledge, this is the first study proposing a cross-country efficiency measurement using a network DEA within the context of the COVID-19 crisis. The study concludes that Estonia, Iceland, Latvia, Luxembourg, the Netherlands, and New Zealand are the countries exhibiting higher mean system efficiencies. Their national COVID-19 strategies should be studied, adapted, and used by countries exhibiting worse performances. In addition, the observation of countries with large populations presenting worse mean efficiency scores is statistically significant.

Eco-efficiency evaluation of Chinese provincial industrial system: A dynamic hybrid two-stage DEA approach

In China, industrial pollution has become an urgent problem for policy makers and enterprise managers. To better support industrial development, we need to determine the effectiveness of policies through efficiency evaluation. China’s provincial industrial system consists of two stages: production and emission reduction. The emission reduction stage is composed of three parallel sub stages: solid waste treatment, waste gas treatment and wastewater treatment. In this process, the treatment capacity of industrial wastewater treatment facilities can be used as carry forward variable, which is not only the desirable output of the previous emission reduction stage, but also the input of the current emission reduction stage. Therefore, this paper proposes a dynamic hybrid two-stage data envelopment analysis (DEA) model for eco-efficiency evaluation of industrial systems, and applies it to a case study of Chinese regional industry. Applying the data collected from 2011 to 2015 to the model, the following conclusions can be drawn: (1) During the whole survey period, the average eco-efficiency was 0.9027. The overall eco-inefficiency of China’s provincial industrial system during the study period is mainly due to low efficiency of solid waste treatment and waste gas treatment. (2) The average eco-efficiency of provincial industrial system increased steadily from 2011 (0.6448) to 2014 (0.6777), but decreased slightly in 2015 (0.5908). (3) The carry forward treatment capacity of industrial wastewater treatment facilities has a remarkable impact on provincial industrial system efficiency scores, especially at the wastewater treatment stage (0.6002 vs 0.3691). (4) Provincial industrial system exists distinct geographical characteristics of low efficiency. This study has important guiding significance for policy makers and enterprise managers who are concerned about industrial pollution control.

Evaluating China's regional energy and environmental efficiency by considering three internal parallel industries

With the rapid development of China's economy, high energy consumption and high pollution emission have become serious problems. To solve these problems, many studies have been done to evaluate energy and environmental efficiency, as the results can provide valuable information to improve performance. However, the previous research mainly evaluates China's regional energy and environmental efficiency by considering each region's industry as a whole system, ignoring the internal structure. In reality, each region mainly includes three parallel types of industry: primary, secondary, and tertiary. Therefore, this paper provides a parallel data envelopment analysis (DEA) approach to evaluate China's regional energy and environment efficiency by considering these parallel industrial systems. The following findings can be obtained based on the empirical results: (1) the overall energy efficiency of China is low, and the inefficiency of the economic system is mainly sourced from the lower energy and environmental performance of the primary industry and the tertiary industry. (2) the introduction of the environmental variable (CO₂) leads to the increase of some backward areas' efficiencies. (3) the energy efficiency of each provincial region is different, and most of them have their own inefficient industries. (4) the total factor productivity of China is declining, mainly because of the decline of technical efficiency.

Fuzzy efficiency evaluation in relational network data envelopment analysis: application in gas refineries

In contrast to classical data envelopment analysis (DEA), network DEA has attention to the internal structure of a production system and reveals the relationship between the efficiency of system and efficiencies of the processes. However, the flexibility of weights and the need for crisp input and output data in the evaluation process are two major shortcomings of classical network DEA models. This paper presents a common weights approach for a relational network DEA model in a fuzzy environment to measure the efficiencies of the system and the component processes. The proposed approach first finds upper bounds on input and output weights for a given cut level and then it determines a common set of weights (CSW) for all decision-making units (DMUs). Hence, the fuzzy efficiencies of all processes and systems for all DMUs are obtained based on the resulting CSW. The developed fuzzy relational network DEA and the proposed common weights approach are illustrated with a numerical example. The obtained results confirm that the fuzzy data affects over the efficiency scores and complete ranking of DMUs. The applicability of the proposed network model is illustrated by performance evaluation of gas refineries in Iran.

Emergy-based ecological efficiency evaluation and optimization method for logistics park

With the rapid development of logistics park, how to evaluate and optimize the ecological efficiency of logistics park to achieve its sustainable development has become a concern of academia. In order to achieve this goal, this paper puts forward a method based on emergy, which processes the data in a unified dimension. By constructing the ecological efficiency evaluation model of logistics park, it quantitatively evaluates the ecological efficiency of logistics park, and analyzes the correlation between various factors and ecological efficiency. The application results of H logistics park show that fuel oil, information technology, net profit, and waste gas are closely related to the ecological efficiency of logistics park, and the correlation coefficients are 0.8248, -0.6949, 0.8544, and 0.7661, respectively. On this basis, the paper puts forward some suggestions to improve the ecological efficiency of the logistics park. This paper provides theoretical and methodological support for the evaluation and optimization of the ecological efficiency of the logistics park.

Industrial three-division network system in China: efficiencies and their impact factors

The industrial production system can be divided into energy consumption (EC), wastewater treatment (WWT), and waste gas treatment (WGT) stages. Based on three stages, this paper presents an empirical investigation on China's industrial efficiencies and the impact factors between 2011 and 2015. Specifically, we apply the network slacks-based measure (SBM) model to evaluate the industrial eco-efficiency, and calculate the division efficiencies via efficiency decomposition approach. Furthermore, the factors affecting the industrial efficiencies are explored through Tobit regression. We find that (1) there is a great potential to improve the eco-efficiency, and for most provinces, the EC efficiencies are highest, followed by the WGT efficiencies, and the WWT efficiencies are the lowest. (2) The efficiencies present obvious area disparities, the eco-efficiency of the eastern area is the highest except for 2012 and 2013, and the eastern area behaves best at the EC stage, while the western area at the WGT stage and the central area fluctuate greatly at the WWT stage. (3) Technological innovation and urbanization level hinder the improvements of eco-efficiency, while economic structure, industrial structure, and economic development level are positive impact factors, especially the industrial structure. Moreover, environmental regulation insignificantly affects the eco-efficiency but exerts a positive effect on the WGT efficiency.

Impact of rating and praise campaigns on local government environmental governance efficiency: Evidence from the campaign of establishment of national sanitary cities in China

BACKGROUND

Ecological and environmental protection is essential to achieving sustainable and high-quality development, which highlights the important role of environmental governance. In terms of the practical actions of environmental governance, the central government in China has carried out continuous rating and praise campaigns, and local governments have actively promoted this effort. However, the related performance consequences have not been empirically investigated. We aimed to verify whether this incentive policy can improve the efficiency of environmental governance and whether this governance method has long-term effects. In addition, we sought to identify mechanisms through which the policy can improve environmental governance.

METHOD

We take the rating and praise campaign of the Establishment of National Sanitary Cities (EONSCs) as a quasi-natural experiment and use the panel data for 174 cities from 2004 to 2016 and the propensity score matching-difference in differences (PSM-DID) method to test the impact of rating and praise campaigns on environmental governance efficiency.

RESULTS

EONSCs campaign can improve the efficiency of environmental governance by 0.7595 (p<0.01), which is significant at the 1% level; the effects are clearly significant during the evaluation process and the year in which cities are named National Sanitary Cities (NSCs) but decrease annually thereafter. The EONSCs campaign has a significant promoting effect on public services provision, such as public infrastructure investment, public transportation and education.

CONCLUSIONS

(1) The rating and praise campaigns can effectively improve the efficiency of environmental governance; (2) the incentive effect is distorted and is not a long-term effect; (3) the impact of the rating and praise campaign of EONSCs on the efficiency of environmental governance is mainly realized through the provision of corresponding public services that are closely related to environmental protection. The findings of this paper provide empirical support for the effectiveness of the central government's rating and praise campaigns and could motivate local governments to actively participate in environmental governance. Moreover, the findings provide an important reference for further improving the rating and praise campaigns and the level of environmental governance.

The metabolic transition of material use and carbon emissions in economically growing Asia: Evidence from 1971 to 2016

The efficient consumption of material and energy resources, with minimal carbon emissions and maximum economic output, is globally significant. This study examines the metabolic transition of resource use and CO₂ emissions in nine of the largest economies of East, South, and Southeast Asia. A data envelopment model has been developed to assess the efficiency of domestic material consumption and CO₂ emissions during 1971-2016 at three levels of analysis. The single-country analysis results reveal that China has made the most rapid efficiency transformation during 1971-2016 followed by Japan and South Korea, while the rest of the countries in South and Southeast Asia have not illustrated significant improvements. Results from the analysis of socio-economically grouped countries show that Japan and Bangladesh are the relatively efficient economies in East and South Asia, respectively. Among Southeast Asian countries, both Indonesia and Malaysia were found to be efficient. Based on the regional analysis comparing all nine countries, Japan has consistently remained a relatively efficient economy while China-despite rapid improvements-remains a relatively inefficient economy. To this end, Japan had the lowest material and CO₂ intensities compared to all other countries. Based on our results, technological advancement, industry structure, and scale of traded goods and services were found to have a significant impact (the impact of per capita income was less pronounced) on a country's effective resource utilization and carbon mitigation.

An integrated data envelopment analysis and life cycle assessment method for performance measurement in green construction management

The construction industry routinely extracts vast quantities of materials and releases deleterious pollutant emissions to the biosphere. In this study, we propose an integrated data envelopment analysis (DEA) and life cycle assessment (LCA) method to measure the performance of eco-friendly building materials in green construction management. Initially, we use the LCA method and environmental impact analysis to identify alternative green flooring systems and relevant sustainability criteria. We then use factor analysis to further evaluate these criteria and choose the most significant sustainability factors. Finally, a DEA model and a new enhanced Russell model (ERM) is proposed to measure the performance of the green flooring systems with factor analysis.

Research on the Spatial Differentiation and Driving Forces of Eco-Efficiency of Regional Tourism in China

Tourism eco-efficiency is an important indicator that has often been applied to measure the quality of green tourism development. This paper takes the 31 provinces of China as examples to analyze regional tourism eco-efficiency. By constructing multiple input and output indicator systems for regional tourism, we estimated the eco-efficiency of 31 provinces in 1997–2016 using an undesirable output model of a slack-based model (undesirable-SBM) for data envelopment analysis (DEA). Then, we analyzed the spatial–temporal evolutionary trends and patterns of the eco-efficiency over 20 years by using the Hot Spot Model and Spatial Center of Gravity Model. Finally, we explored the driving forces internal and external to the tourism eco-economic system using the Panel Tobit Regression Model and Geodetector Model, respectively. The results show that: In the last 20 years, the tourism eco-efficiency of provinces in China declined, though tourism has experienced rapid but extensive development. The western regions of China, which have better eco-environmental conditions, and the southeastern coastal regions, which have higher levels of economic development, have higher tourism eco-efficiency. Regions with lower tourism eco-efficiency show diffusion trends, while regions with higher tourism eco-efficiency are characterized by a lack of obvious space spillover effects. Technology is the core driving force of regional tourism eco-efficiency, while traffic conditions and social civilization levels are key external influence factors leading to improvement of tourism eco-efficiency. The research results reveal the great significance of laws for sustainable green tourism development with different economic levels in the different regions. Our work could provide a reference for similar countries and regions in the world with the rapid growth of tourism or obvious spatial differentiation in socioeconomic development.

Industrial environmental efficiency and its influencing factors in China: analysis based on the Super-SBM model and spatial panel data

The industry sector is not only an important driving force for economic growth but also the largest sector of resource consumption and pollution emission. In this study, we first constructed a super-slack-based measure (Super-SBM) model including the resource consumption and undesirable outputs, and estimated the industrial environmental efficiency (IEE) in China from 2007 to 2016. Afterwards, based on the spatial autocorrelation test and the spatial Durbin model, the spatio-temporal evolution and the influencing factors of IEE were analyzed. The empirical results are obtained as follows: the average IEE from 2007 to 2016 was 0.5176. IEE in the east of China was the highest, whereas it was the lowest in the west. The spatial autocorrelation test showed that the regions with similar levels of IEE in China had significant spatial agglomeration, whereas the local spatial distribution of IEE was unbalanced. The high-high IEE agglomeration areas were located in Liaoning, Jilin, and Inner Mongolia. The low-low IEE agglomeration areas were concentrated in Gansu, Ningxia, and Sichuan. Finally, according to the spatial Durbin panel model and spillover effect decomposition, GDP, FDI, human capital, environmental governance investment, research and development investment, and urbanization have a positive impact on IEE. The industrial and energy consumption structures have a negative impact on IEE. Therefore, the central government should focus on balancing IEE of different provinces and regions, increasing investment in industrial pollution treatment, and encouraging FDI to improve IEE.

Research on measurement and improvement path of industrial green development in China: a perspective of environmental welfare efficiency

The increasing concern about the environmental issue and its serious adverse effects on human health has made China's industrial green transformation being a matter of public concern. In this study, a network slack-based measure (NSBM) was applied to explore China's industrial green development level from the perspective of environmental welfare efficiency (EWE), considering not only the impact of industrial development on environment and economy, but also the impact on human well-being. Based on the data of 30 provincial administrative regions in China from 2004 to 2017, the comprehensive efficiency (CE) of China's industrial sector was measured and decomposed. The results show that the industrial production efficiency (IPE) is much higher than the EWE, and the improvement of the EWE will be the key to realize the green transformation of China's industry. On this basis, considering the effects of spatial interaction, the spatial Durbin model was established to analyze the driving factors of EWE. Finally, this research puts forward promotion path of industrial green development.

Measurement of environmental efficiency in the countries of the European Union with the enhanced data envelopment analysis method (DEA) during the period 2005-2012

In recent years, there has been growing interest in measuring the environmental efficiency of the different territories, countries, and/or nations. This has led to the development of different methods applied to the evaluation of environmental efficiency such as the data envelopment analysis (DEA) method. This method, supported by different studies, allows measuring relative environmental efficiency (eco-efficiency) and is consolidated as a very reliable method to measure the effectiveness of environmental policies in a specific geographical area. The objective of our study is the calculation of the environmental efficiency of the 28 member countries of the European Union (UE) through the DEA method. We will collect the data regarding the last years in which there are reliable comparative data in all. We will study in reference to them, the results of the environmental policies applied in the different countries, in order to make comparisons between countries and classify them according to their environmental efficiency. Using this, two variants of calculation within the DEA method to compare in a contrasted way the results of environmental efficiency for the 28 countries of the EU analyzed and propose possible solutions for improvement. Contributing in this work as main novelty the application of a new variant of the DEA method, which we will call improved analysis method (MAN) and that aims to agglutinate and assess more objectively, the results of the two DEA methods applied. The results show that there are 14 of the 28 countries that have a high relative environmental efficiency. However, we also find countries with very low environmental efficiency that should improve in the coming years. Coinciding precisely in this last group with countries recently admitted to the EU and where environmental policies have not yet been applied effectively and with positive results.